Research on human activity classification strategy based on k-nearest neighbor method

Tianyi Fu; Wangda Tian; Yazhao Yang

doi:10.1117/12.2681188

23 May 2023 Research on human activity classification strategy based on k-nearest neighbor method

Tianyi Fu, Wangda Tian, Yazhao Yang

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 1264541 (2023) https://doi.org/10.1117/12.2681188
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

Although there are a large number of human behavior activity identification data and related wearable technologies, there are still many challenges to realizing the understanding of human behavior. Thus, it is required not only perceive and effectively process the information data of human behavior activities, but also accurately and effectively classify the information data. The core of understanding human behavior is the identification and monitoring of human activities. In this paper, a classification model based on the k-nearest neighbor method was established, and a s-fold cross validation method was proposed. The results showed that the precision of the as-proposed model was about 82%, and the generalization ability was good. Besides, weights were added to the predicted cosine distance, and heuristics were used to search for the best weights, making it was more inclined to fall into the neighborhood of the test set samples. As a result, the overall accuracy could be gradually improved. The prediction accuracy showed an upward trend with the increase of iterations, indicating that this method is indeed helpful to overcome the overfitting problem of human activity classification strategy.

Citation Download Citation

Tianyi Fu, Wangda Tian, and Yazhao Yang "Research on human activity classification strategy based on k-nearest neighbor method", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 1264541 (23 May 2023); https://doi.org/10.1117/12.2681188

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